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Что такое двигатель гудини

Шахматный движок Houdini: краткий обзор программы

Автор: Дядя Валера

День добрый, дорогой друг!

О лидерах в компьютерных шахматах мы уже говорили. Стокфиш, Комодо, теперь появилось новое чудо техники Альфа Зеро. Сегодня в фокусе нашего внимания ближайший преследователь лидеров: Шахматный движок Houdini.

Более того, буквально намендни, в декабре этого года Гудини версии 6.03 переиграл в матче Komodo и был признан новым чемпионом TCEC, неофициальном первенстве мира среди движков. Счет матча 53:47.

Так что, в стане лидеров конкуренция возрастает. И это есть хорошо.

  • Что это за программа?
  • Особенности стиля
  • В какую силу играет движок?
  • Где можно скачать?
  • Как использовать?

Что это за программа?

Гудини/Houdini — компьютерная шахматный движок, предназначенный для ОС Windows. По заверениям авторов, Houdini подходит для любой не слишком старой версии Windows. Программа разработана известным специалистом-программистом Робером Ударом .

Робер «загорелся» интересом к шахматным программам еще в 80-х годах. Благодаря таланту и упорству ему удалось создать по истине уникальный продукт.

Год рождения Гудини — май 2010 года. Движок быстро снискал интерес благодаря убедительным результатам и оригинальной манере игры. Движок практически сразу вышел в лидеры в различных рейтингах, обогнав бывшую в то время во главе списка Rybka .

В начале 2011 года версия движка Houdini 1.5a обыграл Рыбку 23½ на 16½ и был признан лучшей шахматоной программой в начале 2011 года. Через пару месяцев матч-реванш с Rybka и снова успех за Houdini 22:18 .

В 2016 году появилась на свет Гудини версии 5 . По оценкам экспертов, в «пятерке» усилена оценочная составляющая (большая глубина оценки)

В сентябре 17 года появилась версия №6 . По словам автора, улучшены почти все характеристики и сила движка выросла примерно на 60 пунктов ЭЛО.

Поначалу Гудини был некоммерческим начинанием. Ранние версии распространялись бесплатно. Это можно сделать и сейчас на сайте разработчиков до версии движка 1.5 включительно. Следующие версии движка уже заявляются как платные.

Особенности стиля

«На вопрос «Если бы Вы должны были выбрать одного игрока представлять планету Земля в шахматном матче против инопланетян, то кто это был бы из действующих шахматистов?» гроссмейстер Пётр Свидлер, 7-кратный чемпион России, ответил коротко: «Houdini»

Особенность Houdini – удачное сочетание сильной позиционной оценки с лучшим алгоритмом поиска.

По словам автора, название Гудини был выбран из — за позиционного стиля движка, его упорству в защите и находчивости.

По мнению многих экспертов, Гудини уникален своей универсальностью и способностью оценивать множество факторов одновременно.

И самое главное – Houdini способен делать выбор! Он сразу отсекает заведомо невыгодные ходы и фокусируется только на лучших. Можно сказать, движок обладает интуицией. Отсюда репутация Гудини, как непревзойденного блицора.

В какую силу играет движок?

Рейтинг движков по одной из авторитетных версий выглядит так:

Рейтинг ELO 3383 в особых рекомендациях не нуждается. Полагаю, разница в рейтинге с сильнейшим «живым» шахматистом Магнусом Карлсеном ( 2834 ) в 550 пунктов, говорит сама за себя.

Это примерно столько же, сколько разница между мной и тем же Карлсеном.

Очевидно, что с рейтингом 3383 играет последняя версия движка. Однако и предыдущие версии не лыком шиты. Тягаться с такими движками, как Гудини в практической игре на результат , — дело не слишком благодарное.

Другое дело, когда движки бьются между собой. Вот пример:

Houdini Indie for GGJ Online!

Houdini Indie’s procedural node-based workflow offers a smarter way to create high quality game art. Houdini technology is used by AAA studios to take their games to the next level and now this procedural power is available FREE to teams participating in the 2021 Global Game Jam®.

As a game jammer, you are faced with the challenge of building visually rich content with limited time and resources. Houdini Indie’s procedural workflow can help you keep up as you automate repetitive tasks, making it easier to quickly generate larger amounts of quality content.

SideFX is pleased to be sponsoring this year’s game jam and is making a FREE 2-month Houdini Indie license available to help jammers get to the finish line faster!

This Houdini Indie for Global Game Jam license offer will expire at 5pm U.S. PST on Sunday, January 31st, 2021. If you’d like to use Houdini Indie for GGJ, be sure to follow the instructions before this date. Request your license as soon as possible so that you have the most time to learn and use Houdini before GGJ starts.

Please note: the two month period starts from when your request is processed, *not* from when you download the software.

Game Jam Pro Tip: Make sure you download and install Houdini Indie and run through some tutorials BEFORE the game jam begins. Game jam time is very precious and you want to be prepared!

GETTING STARTED WITH HOUDINI INDIE

  • Learn more about Houdini for Game Dev
  • Learn More about Houdini Engine
  • Getting Started with Houdini
  • Houdini Tutorials on SideFX.com

GAME JAM STARTER KIT

SideFX has created a set of procedural game art tools that can be used in Houdini, Unreal Engine, and Unity. This starter kit provides a variety of bread and butter tools that you can use right away to enhance your game environments. These tools can be used inside these host applications using the Houdini Engine plug-ins which you can install at the same time you install Houdini. You can download the Game Jam Starter Kits for free below:

MADE-WITH-HOUDINI GAME JAM VIDEOS

Check out some of the Global Game Jam 2020 games that were made with Houdini!

Check out these interviews with the Houdini Game Jam 2020 winning teams to learn how they used Houdini to build their games in just one week!

I argue that the broader impacts conversation in research evaluation is designed to look like it addresses difficult questions about progress and the good life, whereas in fact it avoids them. In so doing, this discourse does not stay neutral on these questions. Rather, it supplies a default, unexamined answer. The use of normative anchors, or principles, in talk about Responsible Research and Innovation is laudable but inadequate. The problem is, though, that any adequate conversation would seem hopelessly antiquated if not hostile to the assumed goodness of technoscience.

One way research and innovation can be irresponsible is by producing the wrong impacts. Thus, as René von Schomberg ( 2013 ) argues, Responsible Research and Innovation (RRI) would be that which produces the ‘right impacts.’ The unpredictability of research and innovation, especially given the central role of free markets, may make this a practical impossibility. The values plurality of modern society may make this a conceptual impossibility: we could never agree on what counts as a ‘right’ or ‘wrong’ impact.

Von Schomberg thinks we can, however, agree on certain ‘normative anchors,’ which amount to general principles that anyone can endorse. In this way, we can avoid two undesirable outcomes. First, by having explicit discussions guided by these anchors, we can avoid the current market proliferation of impacts that are ‘wrong’ from the standpoint of the anchors. Second, we can avoid entanglement in incommensurable philosophical discussions about the best kind of life and society. We can agree upon and selectively achieve the ‘right’ impacts while still peacefully disagreeing about the ‘good’ life.

I don’t think we can elide the philosophical questions like this, though. In supporting research and innovation, we are already promoting a certain vision of the good and in supporting any given particular project we are putting our thumbs on the scales determining which kinds of lives will be promoted and which will be marginalized. We cannot remain neutral on questions of the good; we can only answer them more or less explicitly.

To see this, consider the discourse surrounding broader impacts. They are often discussed in adversarial terms. The noble researcher guarding academic freedom from anti-intellectual, neoliberal jackals. Or the crusading public servant putting accountability into a system too long premised on blind trust.

But what if ‘broader impacts’ is a sleight of hand? The policymaker is the magician and the researcher is the lovely assistant. She steps into a box and he appears to impale her over and over again with long swords. In reality, though, she is unscathed. Nothing about science or its relationship to society is even touched in the process.

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The whole thing has been an act and you have to look carefully, using the slow motion button on your remote control, to catch the crucial diversion. The scientist says, ‘What I do is vital to social progress even when I don’t intend any benefit.’ The policymaker says, ‘We cannot simply trust that your curiosity is a good way for us to spend our money.’ The scientist pouts as she is led into the box. The policymaker tests the blade of his metrics against his finger nails, ‘Well, we’ll see if you actually have any impact!’ The scientist gives a mock grimace as the sword goes in. What a show!

The diversion comes right away when the word ‘progress’ is mentioned and then promptly elided. Then the words ‘benefit’ and ‘good’ are used and quickly passed over in the same way. The final formulation rests on ‘impact,’ but the initial question was one about progress, that is, whether more knowledge, more science, is always a good thing. If the accountability culture or the broader impacts regime or RRI was something serious, and not just a show, then it would directly confront the questions: What is progress? Which is to say, what is a good impact?

That’s the central illusion: the assumption that any impact is a good impact. At the end of the sixth day, ‘God saw everything that he had made, and behold, it was very good’ (Gen. 1:31). It doesn’t matter that some of the animals eat other animals (so not everything is good from all perspectives), it only matters that stuff was created and it’s dynamic and complex and awe-inspiring.

Consider the mechanical tomato harvester as discussed by Langdon Winner ( 1980 ). In the 1940s, researchers at the University of California developed a marvelous machine that could greatly increase yield and accelerate tomato harvesting over the old hand-picking method. It also cut the cost of harvesting by about $6 per ton, which in turn meant a cheaper tomato for the consumer.

As Winner notes, though, the benefits were not equally distributed. With the introduction of the new technology, the number of tomato harvesters dropped from 4000 in the early 1960s to 600 in the early 1970s. Mechanization eliminated 32,000 jobs, massively transforming rural communities. Attorneys for California Rural Legal Assistance sued the university, arguing that they spent tax dollars on a project that benefited a handful of rich individuals to the detriment of family farms and rural California life more generally. The university argued that to accept these charges ‘would require elimination of all research with any potential practical application.’

Lots of research will have such mixed impacts, creating winners and losers. To delve into this issue would get hairy. Not only could researchers lose lawsuits, but society would have to confront deeply engrained myths about the unassailable goodness of knowledge. Maybe hand picking is better, after all. Yes, it’s harder and more expensive, but family farms and rural communities can survive with their traditions of slow, intentional, place-bound living. There is a certain way of life that has been displaced, but how could we take that seriously? What are we, anti-science, anti-progress?!

From what I can tell, the whole broader impacts conversation is painstakingly arranged to avoid this issue. I credit von Schomberg for at least taking a step toward it with his inclusion of ‘normative anchors.’ But these are so vague and manifold as to be useless in actually determining whether an impact is good or bad or right or wrong. For example, two of the anchors are the ‘promotion of scientific and technological advance’ and a competitive economy, which could act as a blanket greenlight for anything, including tomato harvesters. These would have to be balanced with other anchors such as solidarity and social justice. The conversation von Schomberg imagines falling out from these anchors would inevitably be premised on what kind of lives and society are best – big mechanized agribusiness or small, handcraft farms.

Von Schomberg’s normative anchors are at best something like principles in bioethics: they can start conversations about competing goods, but they cannot replace them. The danger is thinking that we are able to settle such substantive questions by trucking solely in principles. They turn into default, unexamined notion of progress and get baked into certain anodyne goals like ‘economic and social well-being’ (Fealing et al. 2011 , 283). Then, metrics are built atop these goals, as if we know what they mean! Then, viola, the legerdemain is complete as we go about instrumentally linking the means of research to these wholly black-boxed ends. An enterprise that looks like it is about the examination of ends (what good is science?) is transformed into a flurry of means (how do we track cause and effect?).

What we don’t notice is how the swords of metrics, even if they are informed by a discussion of principles or normative anchors, bend when the policymaker thrusts them into the box. Indeed, these metrics (derived from goals like innovation, economic growth, health, sustainability, energy, and national security) are designed to curve perfectly around the shapely body of science. All the metrics are science-shaped swords. That is, they assume a certain vision of progress or the good life premised on modern technoscience. It is a vision that is supposed to give us, as Albert Borgmann ( 1984 ) puts it, a commodious life. Progress means being liberated from the toils of picking tomatoes and enriched with the bounties of perfect, genetically modified fruit made available without regard for season or place. Alternatives within this vision may be more or less explicitly discussed and von Schomberg is right to argue for more explicit discussion. But alternatives to this vision are simply not taken seriously.

Pick any of the principles and it is easy to imagine all sorts of bad or wrong impacts happening after they have been endorsed. Economic growth can cause environmental damage. Innovation can cause anxiety and burnout and erase cultures. High-tech healthcare can bankrupt families without any improvement in quality of life. Energy independence can create local sacrifice zones where extractive activities take place. National security can erode civil liberties. And more generally, technoscientific advance can imperil the planet and fuel a capitalist spiral into massive inequalities. In short, the vision that underwrites the goals that are built into metrics is ambiguous, but it is being taken at face value. Americans are no happier now than they were sixty years ago despite all the progress of mechanized tomatoes and so much more. Yet nothing in the broader impacts regime will reckon with this kind of unsettling reality. It has no sword that doesn’t swerve gracefully around hard questions.

A good deal of talk about RRI these days focuses on reams of un-reproducible and apparently invalid science. Daniel Sarewitz ( 2016 ), for example, argues that responsible research must be more tightly linked to practical problems and more often cashed out in technological solutions. We got our ‘cornucopia of miracles’ (Internet, jet aircraft, cell phones, lasers, satellites, GPS, nuclear and solar power, etc.) not through free curiosity but the heavy guiding hand of the government. Yet nowhere does Sarewitz question the goodness of these miracles. Perhaps in 50 years, this list of miracles will include self-driving cars, autonomous robotic nurses, genetically enhanced humans, and genetically novel organisms made in labs. Is it enough to ensure we bring about these ends efficiently or should we also question the ends themselves?

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Everyone involved in the conversation assumes we know where we want to go (progress!), we just need to get there more efficiently and faster. The assumption is that science churns out a collection of goods that people are free to adopt or decline (see Briggle 2014 ). It’s the great buffet myth: that atomistic individuals can select from an ever-expanding economic pie of technoscientific goodies. Yet obviously, this is not how it works. The farm workers could not just ignore the tomato harvester. The hiker cannot just ignore the interstate highway cutting through his old mountain trail. We can’t still opt for a world without e-mail, atomic weapons, or climate change, whether we consider these miracles or not.

Any metric that defines an impact will carry a normative valence, and that valence bends toward the commodious life. The problem is that this bend is concealed behind the neutral-sounding goals of innovation or ‘economic and social well-being.’ Who could be against that?!

Well, maybe the family farmer.

Creating LODs

To get a game to run smoothly you need LODs! Level Of Detail (LOD) for 3D models means decreasing the complexity of a mesh as it moves away from the camera (or other metrics). A mesh needs a lot of detail when being inspected from nearby, but does not need as much detail when being looked at from a distance to maintain its look.

Making LODs can be quite tedious, especially if they are for geometry that aren’t considered “hero objects”, such as characters or key objects in gameplay. Nobody likes making LODs for small props that are scattered around and only really function as filler objects. So why don’t we all collectively agree to generate these semi-automatically?

Requirements

To get proper LODs, we need to first have a piece of geometry that functions as our LOD0. The goal is to generate copies in decreasing levels of complexity based on that input. While doing so, we need to preserve the UVs or regenerate them to consolidate the materials.

As an example we’ll be running this mesh from Quixel Megascans through the LOD Create tool from SideFXLabs. By default it will generate polyreduced versions of it, and all the artist needs to do is specify how much each LOD should be reduced by.

By clicking the “Debug all LODs” checkbox, we can see the total chain of generated meshes. As expected, each LOD is reduced in complexity and even has an impostor as the last LOD. Impostors are basically just an orthographic 2D render of the geometry, that gets assigned to a billboard mesh in the distance (very useful for rendering a forest of trees cheaply).

Once you tweak the values to your liking, you hit export and import it to your engine of choice. That’s it. The tool even has a preset system so you can import your own pre-made configurations for easy processing of many assets. The nice thing about this is that you could once again use PDG to process a whole library of assets at once, and tweak the results. Another benefit of using this tool is that it is fully open source, meaning you can dive inside and change any of the steps used to generate the LODs. Don’t like how it polyreduces? Change the approach to use your own.

The Houdini of CSS

Julian Wilkison-Duran

I have been a full stack developer at Blue Triangle for a little over a year. Previously I worked in the government and healthcare sectors as a Scientist and Engineer.

As a website developer, when I hear about multimedia technology on the web, I conjure up memories of things like Java Applets and Flash sites. They made the internet look more aesthetically pleasing and functional but also introduced significant performance and security issues. Flash brought 2D animation to the web since the beginning of the web, and Java Applets brought 3D graphics to the web and even at one-point outperformed JavaScript and HTML elements. So why did these technologies die?

The introduction of HTML 5 on October 28, 2014, killed the need to have external plugins for multimedia objects. HTML 5 introduced web application programming interfaces (API) for multimedia objects controlled directly by the browser. JavaScript now had access to the WebGL 3D interfaces that Java Applets had as well as a safer API to access files. This is what removed the need to have Java Applets that year. The new APIs also included a means to manipulate 2D images and create simple animations. This would have replaced Flash, except for the fact that it had a huge following, a better user interface, and interactivity built-in. What eventually killed Flash was Apple’s refusal to support the plugin on their mobile phone browsers. As of last year, Adobe has stopped support completely for Flash. So how do developers add multimedia sites today?

Today web developers rely on HTML 5 web APIs for multimedia aspects on their sites. The problem with these APIs is compatibility between various web browsers and even web browser versions. Many of these APIs were not fully supported by browsers until the beginning of this year. JavaScript has been at the forefront of this. Modern JavaScript frameworks like Angular and React have made these APIs much easier to use and have polyfills for browsers that do not support specific APIs. This has taken JavaScript from just a DOM manipulator to a Graphic’s manipulator. But what if you did not have to wait for browsers to adopt a particular feature without polyfills? What if you had direct access to the browser rendering engine? Then you could render virtually anything in the browser at breakneck speeds.

Enter Houdini, the JavaScript APIs that give direct access to the browser’s CSS rendering engine. Houdini allows developers to access the CSS Object Model (CSSOM) much like they would the DOM in JavaScript. The Houdini code does not wait for the first render like inline styles; instead, it occurs during the first render of the page. Developers can create renderable styles before any other scripts load. Its StylePropertyMap can access every element and style sheet in the DOM. To create a Houdini script to manipulate the CSSOM, you must implement a worklet. A worklet is much like a JavaScript Service Worker in that it is a low-level API to access browser methods that is portable and modular. Worklets give you access to the browser’s render engine, where service workers provide you with access to the browser’s caching engine. This access gives developers control over some powerful methods. This is all accomplished without the need for frameworks, postprocessors, or preprocessors.

CSS Parser API

With access to this method, you can parse any text document and turn it into some form of CSS. Think typescript for CSS or even SASS, but that compiles automatically in the browser as fast as a regular CSS document would load. CSS Properties and Values API This allows developers to create custom CSS properties, for instance, creating a property called font-awesomeness with values like fabulous, ok, and meh that translate to real renderable objects.

CSS Typed OM

It takes the overhead out of typing the CSSOM for JavaScript Objects making the whole API more performant.

CSS Painting API

It lets you literally draw anything on the screen anywhere, think Canvas or SVG, only it renders before either of those, and you can render in any element border or background.

The implications for having access to such APIs are great for web performance as a whole. You can draw anything to the screen before anything else loads as fast as CSS, creating animations outside the current window’s context asynchronously. Having the ability to perform all of this without having to worry about which browser the user is utilizing is huge. It will reduce the weight of web applications that have to polyfill for unsupported browsers and get rid of bulky frameworks that must wait for the first browser render and slow pre- and post-processors.

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Disadvantages of Using Chess Engines

There is one major downside of using chess engines! They don’t care about winning the game but try to achieve the highest possible assessment in their merit function.

A computer isn’t really interested in subjectively dangerous counterplay that objectively doesn’t pose a threat. Hence, it is vital not only to look for the move with the highest ranking while analyzing with chess engines but also to concentrate on the easiest way to win.

When you have the choice between a complicated mate in 8 moves sacrificing material and a simple way to win the opponent’s queen with an easily won position, you should always decide for the latter.

Unlike Chess Engines We Are Not Machines

People often have a tough time to turn objectively won positions into a full point. Thus, in winning positions it is essential to stay highly concentrated and to prevent counterplay, instead of traveling mentally to the calculation of the allegedly won ELO points and the next game in the tournament.

Moreover, it is dangerous to trust the evaluation of chess engines. A position which an engine assesses as 0.00 is not necessarily an easy draw for both sides.

It can also mean that one side has to eliminate the opponent’s strong initiative with 10 precise moves in a row. Practically speaking, this is an extremely difficult task.

Hence, it is important to understand why computers give certain evaluations. It should also be noted that chess engines are not able to detect fortresses.

You can take a look at the position on the right. Black managed to create a fortress. He can just move his rook between f6 and d6. If White gives checks with his queen, Black’s king always stays next to the pawn.

White can’t make any progress.

One of the biggest criticisms of chess engines in the past was their inability to accurately evaluate such fortresses.

Such a position might well have received a +2.00 evaluation not very long ago. However, thanks to the continuing advancements in chess engines, Stockfish 13 now rates this position even no matter which side is to move.

There Is No Substitute For Putting in the Hard Work

The right tool for the right job is a wise saying we would do well to heed even in our technological age. Chess engines are a great aide to chess players, especially if you train alone.

However, legitimate chess improvement requires a level of discipline that prefers to avoid shortcuts and opts for the steeper path to real knowledge and understanding.

More and more chess players become too lazy to think on their own. Instead, they almost always look at the engine’s evaluation.

This superficial approach to chess study will not only fail to improve your chess game, but it will also make you worse by enforcing bad habits.

Chess games among human beings involve a lot more subtleties than a simple computer evaluation like +0.51 can tell you.

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Prior to joining Strasburg Rail Road, you were an Executive Chef for Disney. Tell us about your career. I started cooking at The California Grill in 1996. That was the start of signature fine dining experience in existence today at Walt Disney World. I am very proud of that. Over the years, I have had…

October 14, 2020

Strasburg is the perfect place for a quick day trip or long weekend for families, couples, or anyone looking to enjoy the great outdoors of Amish Country. As the most historic town in Pennsylvania Dutch Country, Strasburg is home to quaint shops, cozy places to stay, delicious local food, Amish farmland, local artisans, and historic sites you won’t want to miss. Hours of adventure are just a short drive away! Things to Do in Strasburg, PA For a small village, Strasburg is packed with things to do and see. Whether you’re interested in history, culture, local cuisine, new discoveries, or engaging activities, you’ll find it at Strasburg. Strasburg Rail Road One of the most popular attractions in Strasburg is the Strasburg Rail Road America’s oldest short line. People have driven to Strasburg to ride the 4.5-mile track aboard an authentic…

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